ArticleGenome medicine2024
Identifying latent genetic interactions in genome-wide association studies using multiple traits.
Article in Genome medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed.
- Gene-Environment Interaction Loci Associated with Refractive Error: SCAMPI Analysis.Ophthalmology science · 2026Article
- MAGIC populations: a next-generation framework for dissecting complex quantitative traits and accelerating molecular breeding in crops.Frontiers in plant science · 2026Review
- A powerful framework for differential co-expression analysis of general risk factors.Bioinformatics (Oxford, England) · 2025Article
- Article
- Marginal interaction test for detecting interactions between genetic marker sets and environment in genome-wide studies.G3 (Bethesda, Md.) · 2025Article
- SCAMPI: A scalable statistical framework for genome-wide interaction testing harnessing cross-trait correlations.bioRxiv : the preprint server for biology · 2024Article
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Authors and funding
6 authors.
Funding
Abstract
The "missing" heritability of complex traits may be partly explained by genetic variants interacting with other genes or environments that are difficult to specify, observe, and detect. We propose a new kernel-based method called Latent Interaction Testing (LIT) to screen for genetic interactions that leverages pleiotropy from multiple related traits without requiring the interacting variable to be specified or observed. Using simulated data, we demonstrate that LIT increases power to detect latent genetic interactions compared to univariate methods. We then apply LIT to obesity-related traits in the UK Biobank and detect variants with interactive effects near known obesity-related genes (URL: https://CRAN.R-project.org/package=lit ).
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